| --- |
| license: apache-2.0 |
| base_model: Helsinki-NLP/opus-mt-ar-en |
| tags: |
| - generated_from_trainer |
| metrics: |
| - bleu |
| model-index: |
| - name: bot_train_am_7 |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # bot_train_am_7 |
| |
| This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ar-en](https://huggingface.co/Helsinki-NLP/opus-mt-ar-en) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.5408 |
| - Bleu: 33.1944 |
| - Gen Len: 12.2599 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 15 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| |
| | 2.2203 | 1.0 | 984 | 1.7126 | 25.9506 | 12.0381 | |
| | 1.5778 | 2.0 | 1968 | 1.5978 | 28.5264 | 11.8927 | |
| | 1.3114 | 3.0 | 2952 | 1.5466 | 30.454 | 12.0183 | |
| | 1.1266 | 4.0 | 3936 | 1.5216 | 31.2974 | 12.1139 | |
| | 0.9856 | 5.0 | 4920 | 1.5155 | 31.7487 | 12.0509 | |
| | 0.8635 | 6.0 | 5904 | 1.5146 | 32.1394 | 12.1887 | |
| | 0.7871 | 7.0 | 6888 | 1.5223 | 32.7087 | 12.2431 | |
| | 0.7064 | 8.0 | 7872 | 1.5384 | 33.1917 | 12.1409 | |
| | 0.6409 | 9.0 | 8856 | 1.5408 | 33.1944 | 12.2599 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.41.2 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
